The invention relates to a method for reconstructing linear structures present in raster form. Such linear structures can be used to identify persons. In order to identify persons, use is usually made of their fingerprints, but also of other linear structures such as those of the retina, the vascular plexus of the retina of the eye. Use can also be made of the linear structure in the iris of the human eye for the purpose of a unique identification of a person.
In order to be able to use the said linear structures to identify persons, a multiplicity of such linear structures must be combined in a database. A linear structure of a person to be identified is then compared with the content of this database. In the meantime, ever more voluminous collections of linear structures are exceeding the possibilities for carrying out visual comparisons in an acceptable time. However, because of the rapid developments in the fields of storage media and the techniques of digital image processing, tools are available which permit the design of powerful recognition systems.
Barry Blain, Introduction to Fingerprint Automation, Home Office Police Department, Police Systems Research & Development Group, Publication No. 1/93, 1993 discloses a method by means of which the line directions can be determined. In order to determine the line direction, the image is parqueted into slightly overlapping subregions with a size of 20.times.20 pixels, four to six pixels overlapping at the edge of the subregions. After determination of the direction, which is performed by regional Fourier transformations, a directional smoothing with subsequent binarization is undertaken. The threshold values for the binarization are determined by histograms in the subregions. The binary image thereby produced still contains prominent defects, which are later corrected by means of diverse consistency criteria. It is not always possible to expect an error-free correction of the defects, for example the merging of regions which do not belong together, or the separation of lines.
In order to achieve a high processing rate in the recognition of linear structures, the storage of essential information such as, for example, the precise position and shape of lines as well as their thickness, is frequently dispensed with during the storage of linear-structure data. Moreover, the linear structures to be coded are frequently present only in a reduced image quality. In subregions, the image is for example blurred or has insufficient contrast. In the case of coding in accordance with the prior art, the linear structure in such regions is estimated. However, it is then no longer possible to recognise from the stored binary image of the linear structure the degree of reliability with which the individual image sections were generated from the basic image pattern.